HighVulnerability
CVE-2025-14930: Hugging Face Transformers GLM4 deserialization of untrusted data
- Source
- NVD(opens in a new tab)
- Identifier
- CVE-2025-14930
- Published
- Record updated
- Known exploitation
- Not listed in the CISA Known Exploited Vulnerabilities catalog at the last check.
- EPSS
- 0.3%
Summary
CVE-2025-14930 is a remote code execution flaw in Hugging Face Transformers' GLM4 weight parsing. The flaw stems from missing validation of user-supplied data, leading to deserialization of untrusted data. An attacker who gets a target to visit a malicious page or open a malicious file can execute code in the context of the current process.
Mitigation
The source does not state a fix yet. Check the original advisory for updates.
Related items
- HighCVE-2026-119120: Crawl4AI Docker API lets clients choose the HuggingFace model it loadsSame vendor · NVD/CVE Database
- HighGHSA-wf6j-7hvr-gr93: Hydra legacy target blacklist permits unsafe PyYAML loadingSame vendor · Hugging Face Security Advisories
- MediumCVE-2026-100653: vLLM unpinned Hugging Face artifact loads for FunAudioChat and Tarsier2Same vendor · NVD/CVE Database
- HighGHSA-3hmm-rh5q-gwwr: LMDeploy vulnerable to arbitrary code execution via eval() of untrusted quant_dtype in model config loadingSame vendor · Hugging Face Security Advisories
- MediumCVE-2026-80047: Hugging Face Transformers writes remote Python files to disk before trust checkSame vendor · NVD/CVE Database